Instructions to use dhhd255/EfficientNet_ParkinsonsPred with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dhhd255/EfficientNet_ParkinsonsPred with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="dhhd255/EfficientNet_ParkinsonsPred")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("dhhd255/EfficientNet_ParkinsonsPred") model = AutoModel.from_pretrained("dhhd255/EfficientNet_ParkinsonsPred", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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# EfficientNet Parkinson's Prediction Model 🤗
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This repository contains the Hugging Face EfficientNet model for predicting Parkinson's disease using patient drawings with an accuracy of around
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Made w/ EfficientNet and Torch.
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## Overview
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# EfficientNet Parkinson's Prediction Model 🤗
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This repository contains the Hugging Face EfficientNet model for predicting Parkinson's disease using patient drawings with an accuracy of around 83%.
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Made w/ EfficientNet and Torch.
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## Overview
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